Implicit integral equations for modeling systems with a transport delay

International audienceIn this chapter, we present a particular class of transport delay systems (e.g. systems involving transportation of material), in which the delay is definedthrough an implicit integral equation. To illustrate the practical interest of this class, experimental use of such models is presented for two different examples of physical systems, both from the field of automotive gasoline engines (specifically, exhaust gas recirculation and exhaust catalyst thermal dynamics). We also discuss related control challenges, together with some solution

System identification for control of temperature and humidity in buildings

HVAC systems are widely used to provide a good indoor air quality in buildings. Buildings stand for a substantial part of the total energy consumption in developed countries, and with an increased focus on cost reductions and energy savings, it is necessary to use intelligent and energy-efficient controllers. Accurate models describing the dynamics of the building system is a good basis for intelligent control. In countries like Sweden there are large seasonal variations in the outdoor climate, and these variations interfere with the indoor condition and thus affects the control. In this thesis the seasonal variations are investigated, and the aim is to determine how these differences affect identified models for control of temperature and relative humidity in buildings. Two MISO (Multiple Input-Single Output) systems and one MIMO (Multiple Input-Multiple Output) system is used to describe the mean room temperature and relative humidity in a selected room in the Q-building at KTH, Stockholm. The models are identified following the black-box approach, and data from four different months during 2014, representing the winter, spring, summer and autumn season respectively, are collected and preprocessed. The validation of the identified models for the humidity and temperature, shows that it is possible to use identical orders and input delays for all seasons, with good results. Based on the results one would not recommend using models with the same model parameters throughout the year, since the conditions varies too much from season to season

Control and State Estimation of the One-Phase Stefan Problem via Backstepping Design

This paper develops a control and estimation design for the one-phase Stefan problem. The Stefan problem represents a liquid-solid phase transition as time evolution of a temperature profile in a liquid-solid material and its moving interface. This physical process is mathematically formulated as a diffusion partial differential equation (PDE) evolving on a time-varying spatial domain described by an ordinary differential equation (ODE). The state-dependency of the moving interface makes the coupled PDE-ODE system a nonlinear and challenging problem. We propose a full-state feedback control law, an observer design, and the associated output-feedback control law via the backstepping method. The designed observer allows estimation of the temperature profile based on the available measurement of solid phase length. The associated output-feedback controller ensures the global exponential stability of the estimation errors, the H1- norm of the distributed temperature, and the moving interface to the desired setpoint under some explicitly given restrictions on the setpoint and observer gain. The exponential stability results are established considering Neumann and Dirichlet boundary actuations.Comment: 16 pages, 11 figures, submitted to IEEE Transactions on Automatic Contro